Instructions to use ProbeX/Model-J__MAE__model_idx_0236 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__MAE__model_idx_0236 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__MAE__model_idx_0236") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__MAE__model_idx_0236") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0236", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 269ac72479fa22100c90137bbfc5b8830c993f5531433d4211a451caec4e72b3
- Size of remote file:
- 5.37 kB
- SHA256:
- 03f4d46e26bb4ff7ec1089c50b5dc17a640d3446a71469c04a4a233c78a76d0c
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